It has been long pursued for more image details in a larger imaging area of biological samples in the field of optical imaging. However, imaging of, for example, mice brain of small size requires a day to obtain the whole brain data using optical microscopy in the prior art. Although an interval of axial sampling is omitted, it still takes several days or even more than ten days to obtain a complete fine structure of the brain sample. For larger monkey brain and human brain samples, the imaging time will be greatly increased, thus leading to various instability problems. For example, if the embedding medium for samples is soaked for too long, changes in physical properties of the samples will occur, resulting in deformation, collapse and even fall of the samples. This affects the integrity of data set and consumes a lot of human and material resources. Hence, there is a demand for reduction of redundant data acquisition which can reduce the total acquisition time so as to improve the stability of the imaging system.
Currently, a regular cube is usually employed in the existing optical microscopic imaging system to define an imaging area, i.e., an imaging area that contains a maximum sample area in each transverse coronal plane from top to bottom to ensure the integrity of the whole brain data set. In this manner, a large number of redundant data is acquired, reducing the acquisition efficiency and extending the acquisition time. At the same time, the retention of redundant data takes up a lot of space used to store data.
Some microscopic imaging systems reduce the acquisition of redundant data using manual modification of imaging areas. However, this results in three problems: first, manual modification requires a lot of labor due to a long imaging time; second, it is difficult to realize real-time modification, and the imaging areas are usually altered at a fixed interval so the redundant data still exists; third, it is prone to incorrectly operate and cause system error, resulting in data loss.
Therefore, there exists some defects in manual modification for microscopic imaging area of the biological samples, such as consumption of human resources, difficulty in real-time modification and misoperation. In addition, the existing automatic modification for microscopic imaging area of the biological samples has problems such as high error rate and lack of self-checking ability. Thus, it is necessary to propose a novel method for automatically altering the imaging area in the microscopic imaging of the biological samples.